Tinia Halfar - TransUnion - Data Strategy presentation at the Chief Data Officer Forum, Africa

How to develop a vision and strategic plan for data in the organisation

Tinia Halfar

Setting the Data Office direction

6 JUNE 2016

2 | © TransUnion. LLC All Rights Reserved

Why should I invest in data?

Leverage data to predict changes in the marketplace

Personalise your customer experience

Improve internal operations

Prevent potential fraud

The average cost of a corporate data breach increased 15% in the last year

Targeted marketing

Data is growing and becoming more disparate

Bad data quality is costing your business…a lot

Your competition is investing in data and analytics

Data is the best tool for process improvement and optimisation

If analysts are spending 40% of their time manipulating data and creating reports, how much time are they actually spending analysing the data?

A study found that the cost of bad data was equal to between 10% - 25% of the organisation’s revenue

Sources: https://www.import.io/post/5-undeniable-reasons-to-invest-in-data-today/ , http://knowlton-group.com/5-reasons-to-invest-in-data-and-analytics-in-2016/

Giving your data a meaningful voice is about choosing to invest in the right human skills

What is a Data Office?

Steps to articulate your Data Office

Direction

Break-away workgroups

AGENDA

1

2

3

https://www.import.io/post/5-undeniable-reasons-to-invest-in-data-today/



http://knowlton-group.com/5-reasons-to-invest-in-data-and-analytics-in-2016/




What is a data office?

The Data Office is accountable for getting their organisations to treat data as an enterprise asset (1)

Enterprise Information Management specialises in finding solutions for optimal use of information within organisations (2)

Enterprise information management is a set of business processes, disciplines and practices used to manage the information created from an organisation's data. (3)

Enterprise data management is a concept that refers to the ability of an organisation to precisely define, easily integrate, and effectively retrieve data for both internal applications and external communication (4)

The data office effectively manages, enhances and publishes data and information assets to the business community.

Sources: 1. Http://www.information-management.com/news/news/key-considerations-in-establishing-a-chief-data-office-10025545-1.html 2. https://en.wikipedia.org/wiki/Enterprise_information_management 3. http://searchcontentmanagement.techtarget.com/definition/enterprise-information-management-EIM 4. https://en.wikipedia.org/wiki/Enterprise_data_management

ALSO REFERRED

TO AS:

Enterprise Data /

Information Management

The Chief Data Office

Business Intelligence

Hub

Big data team

http://www.information-management.com/news/news/key-considerations-in-establishing-a-chief-data-office-10025545-1.html

http://www.information-management.com/news/news/key-considerations-in-establishing-a-chief-data-office-10025545-1.html

https://en.wikipedia.org/wiki/Enterprise_information_management

http://searchcontentmanagement.techtarget.com/definition/enterprise-information-management-EIM

https://en.wikipedia.org/wiki/Enterprise_data_management

https://en.wikipedia.org/wiki/Enterprise_data_management


Session Outcome: 5 steps to articulate your data office direction

The 5 step process navigates your thinking and highlight concepts to consider in order to articulate your data office direction.


Porter’s Generic Strategies Cost Leadership Differentiation Focus

Description

• Superior profits through lower costs

• Costs can be reduced through improving operational efficiencies

• Effective process controls• Target broad markets

• Creating a product or service that is perceived as being unique throughout the industry and more attractive to a particular target market

• Differentiation from competitors' products as well as a firm's own products

• Concentrating on a limited part of the market

• Enjoys a high degree of customer loyalty

• Premise that a segmented group can be better served by focusing entirely on it

Core Competencies

Required

• Operational excellence • Vendor and supply chain

management (JIT)• Forcasting and planning

• Customer insights• Innovation and research• Marketing analytics• Creative product dev

• Segmentation analytics• Loyalty behaviour • Real-time, personalised

analytics

Example

Business StrategyIdentify your key business goals and objectives

Business Strategy

Data Vision

Data Capability

Maturity Analysis

Delivery Model

Sources: 1. http://www.slideshare.net/dipalij07/porters-generic-strategies-with-examples; 2. https://en.wikipedia.org/wiki/Product_differentiation 3. https://en.wikipedia.org/wiki/Cost_reduction

http://www.slideshare.net/dipalij07/porters-generic-strategies-with-examples

http://www.slideshare.net/dipalij07/porters-generic-strategies-with-examples

https://en.wikipedia.org/wiki/Product_differentiation

https://en.wikipedia.org/wiki/Product_differentiation

https://en.wikipedia.org/wiki/Cost_reduction

https://en.wikipedia.org/wiki/Cost_reduction


I need to adhere to regulatory / compliance requirements

Highly regulated environments – Example: Credit Bureaus and Banks - Twin Peaks model of financial sector regulation,

POPI, Treating Customer Fairly, BCBS 239 Risk data aggregation and reporting.

I want to use my data to make better decisions

Identify customer acquisition strategies. Determine cross sell opportunities. Drive actions through propensity modelling.

Use of predictive analytics to improve decision making. Widely adopted MI reporting. Interactive BI dashboards and

self-service views.

I want to use my data to improve customer experience

360° / single view of a customer. Personalisation via segmentation to enable bespoke and tailor-made

experiences. Moving from a product-centric approach to a customer-centric approach. Frictionless, on-demand and

real-time customer experiences.

I want to monetise my data by creating new products and services

Building and commercialising data products.Selling data as a service or white label your data office

technology or capabilities.

What is your Data Vision?What kind of data office are you setting up?

Business Strategy

Data Vision

Data Capability

Maturity Analysis

Delivery Model

The structure and focus of your data office depend on the objectives that you need to achieve as well as your business strategy. Four distinctly different data office objectives are represented here and you can aspire to achieve more than one of these objectives.








self-service views.









Business Strategy

Data Vision

Data Capability

Maturity Analysis

Delivery Model


Cost Leadership strategy








self-service views.









Business Strategy

Data Vision

Data Capability

Maturity Analysis

Delivery Model


Differentiation strategy








self-service views.









Business Strategy

Data Vision

Data Capability

Maturity Analysis

Delivery Model


Focus strategy


Data Capabilities

Design and BuildThe capabilities toplan your delivery

ManageThe capabilities to manage your delivery

PublishThe capabilities to expose the data to the end-user

Business Strategy

Data Vision

Data Capability

Maturity Analysis

Delivery Model

Business Intelligence

AnalyticsDiscovery Science

Visualisation

Geospatial Predictive

Business Rules

Governance

Performance Privacy

QA Security

Stewardship

Warehouse

Meta Data

Reference and MDM

Architecture Integration Modelling Development Engineering

Management Information

Internal data sources External data sources

Publish to end user

There are many data competencies required to enable raw data to be transformed and packaged into insight and information for the end-user to digest. The data competencies which build on each other are grouped into 3 categories:


Capabilities you might want to include

Data Capabilities Regulation DecisionMaking

Customer Experience

MonetiseData

Data ArchitectureData Modelling

Data Governance

Data Warehouse ManagementData Quality Management

Meta Data ManagementBusiness Rules Management

Management Information

Business IntelligenceData Visualisation

Data AnalyticsData Science

Predictive Analytics

Business Strategy

Data Vision

Data Capability

Maturity Analysis

Delivery Model

Illustrative


Data Capability Maturity Assessment

Business Strategy

Data Vision

Data Capability

Maturity Analysis

Delivery Model

Once you understand the objective of your data office you need to identify the competencies required to achieve this. In order to prioritise your efforts you need to perform a maturity assessment.


Key Components of Maturity Assessment and Target Setting

DataCompetencies

Current Level

Target Level

GapImportance

Data Science 0 3 3 1

Data Architecture 1 3.5 2.5 3

Data Governance 1 4 3 4

Predictive Analytics 1 2 1 1.8

Data Modelling 1.5 2.5 1 3.5

Business Intelligence 1.5 3.5 2 4

Warehouse Management 3 4.5 1.5 2.5

Management Information 3 3 0 3

Business Strategy

Data Vision

Data Capability

Maturity Analysis

Delivery Model

AS-ISEvaluate your current

capability maturity levels

TARGETThe desired level of maturity

required

GAPThe distance between where a process level

resides and where it needs to be

IMPORTANCEHighlight priority

capabilities by importance: Rating range 1-4. 1= least

important, 4=critical

You can effectively determine your priorities by assessing your current level of maturity and setting the target level required to achieve your objective. Additionally, you need to rank the importance of each one of the capabilities.

Illustra

tiveRatings: Level 0 – Non-existentLevel 1 – Initial / Ad HocLevel 2 – Repeatable but IntuitiveLevel 3 – DefinedLevel 4 – Managed and measurableLevel 5 – Optimised


Prioritise your next key initiatives

0 1 2 3 40

1

2

3

4

5

Data Science

Data Architec-ture

Data Gov-ernance

Predictive ana-lytics

Data Modelling

Business Intel-ligence

Warehouse Management

Management In-formation

GAP

IMPO

RTAN

CE

Once you understand your key priorities you need to determine how you will reach the target level for each:

Define resource requirementsSourcing strategy: Build vs. BuyAligning architecture requirements to your data strategyRobust change management programme

Business Strategy

Data Vision

Data Capability

Maturity Analysis

Delivery Model

Below, the capabilities were mapped according to the gap between the current and target level of maturity as well as the importance of each. By plotting this on a chart you can easily identify the key priority areas.


Data Office Delivery model design decisions

Localised

Hub and Spoke

FullCentralisation

Local instance, with selected components

delivered from centralised location

Local instance with LOB delivery and

control

Capability fully controlled and delivered

from a centralised location

Centre of Excellence

Local instance, but governed through

CoE frameworks and standards

Description

• Total central control and management oversight

• Cost savings related to system infrastructure economies of scale

• Specialised skill sets and improved security

• Local instance and process execution improves LOB performance

• Centralised control of key oversight and administrative functions efficiency

• System ownership is shared

• No integration where there is a big difference in product / service

• Data movement performance advantage due to local connectivity

• Faster integration with local systems

• Benefits of autonomy but with centralised controls and standards

• Serve as an advisory role• First step to change from a localised model

to a centralised model

Country Solution Centralised Solution CoEKey

Benefits

• Who will be responsible for data

– Business vs. IT

• Executive buy-in

• Compelling vision for change

• Monetary benefit vs. Investment

• Data vs. Information

• Risks and regulation

• Complexity

Business Strategy

Data Vision

Data Capability

Maturity Analysis

Delivery Model

Other Considerations

The final step in articulating your data office direction is to decide on your delivery model as well as other key considerations to take into account.

Articulate your Data Office direction

Business Strategy

Data Vision

Data Capabilities

Maturity Analysis

Delivery Model

Break-away groups

Data & Analytics

Tinia Halfar - TransUnion - Data Strategy presentation at the Chief Data Officer Forum, Africa